This report examines the phenomenon of "churn" in public benefit programs, where eligible participants temporarily lose benefits due to administrative processes, analyzing its impact on both recipients and state agencies, and suggesting strategies to reduce its occurrence.
Accessing safety net benefits can involve complicated and duplicative processes that create barriers to access. Using cross-enrollment strategies can minimize the difficulties community members face in getting access to life-saving resources.
Webinar that shares Nava’s partnership with the Gates Foundation and the Benefits Data Trust that seeks to answer if generative and predictive AI can be used ethically to help reduce administrative burdens for benefits navigators.
In early 2023, Wired magazine ran four pieces exploring the use of algorithms to identify fraud in public benefits and potential harms, deeply exploring cases from Europe.
Describes the Principles of a Human-Centered Safety Net: Many Welcoming Doors, Easy to Understand, Clients Can Make Informed Decisions, Responsive to Changing Needs, Simple Actions
Policymakers, program administrators, federal leaders, researchers, and advocates are increasingly focused on using administrative data to build evidence for improving government programs. Achieving this goal requires accessible data sources and the capacity to use them, yet stakeholders have little information about the baseline level of state capacity in these areas. How does one measure concepts such as “effective data use” and “analytic capacity?” This brief reports findings from a pioneering and comprehensive needs assessment that examined the capacity of Temporary Assistance for Needy Families (TANF) programs in 54 U.S. states and territories to analyze data used for program improvement, monitoring, and evidence-building. The needs assessment provides a foundation for technical assistance and continued improvement for the TANF program and may also provide valuable insights and frameworks for other state-administered human services programs.
Unofficial calculator allowing users to see if they may be eligible for Medicaid, CHIP, or savings on health insurance. The calculator can be embedded on other websites.
This report explores the role that academic and corporate Research Ethics Committees play in evaluating AI and data science research for ethical issues, and also investigates the kinds of common challenges these bodies face.
This primer is written for a non-technical audience to increase understanding of the terminology, applications, and difficulties of evaluating facial recognition technologies.
